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Focus testing effort on highest-risk areas using risk assessment and prioritization. Use when planning test strategy, allocating testing resources, or making coverage decisions.
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インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/proffesor-for-testing/sentinel-api-testing --skill risk-based-testingコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。
WCAG 2.2 compliance testing, screen reader validation, and inclusive design verification. Use when ensuring legal compliance (ADA, Section 508), testing for disabilities, or building accessible applications for 1 billion disabled users globally.
AI agents as force multipliers for quality work. Core skill for all 19 QE agents using PACT principles.
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SOC 職業分類に基づく
SKILL.md を表示中
| name | risk-based-testing |
| description | Focus testing effort on highest-risk areas using risk assessment and prioritization. Use when planning test strategy, allocating testing resources, or making coverage decisions. |
| category | testing-methodologies |
| priority | high |
| tokenEstimate | 1000 |
| agents | ["qe-regression-risk-analyzer","qe-test-generator","qe-production-intelligence","qe-quality-gate"] |
| implementation_status | optimized |
| optimization_version | 1 |
| last_optimized | 2025-12-02T00:00:00.000Z |
| dependencies | [] |
| quick_reference_card | true |
| tags | ["risk","prioritization","test-planning","coverage","impact-analysis"] |
<default_to_action> When planning tests or allocating testing resources:
Quick Risk Assessment:
Critical Success Factors:
Risk Score = Probability (1-5) × Impact (1-5)
| Score | Priority | Effort | Action |
|---|---|---|---|
| 20-25 | Critical | 60% | Comprehensive testing, multiple techniques |
| 12-19 | High | 25% | Thorough testing, automation priority |
| 6-11 | Medium | 10% | Standard testing, basic automation |
| 1-5 | Low | 5% | Smoke test, exploratory only |
| Factor | Low (1) | Medium (3) | High (5) |
|---|---|---|---|
| Complexity | Simple CRUD | Business logic | Algorithms, integrations |
| Change Rate | Stable 6+ months | Monthly changes | Weekly/daily changes |
| Developer Experience |
| Senior, domain expert |
| Mid-level |
| Junior, new to codebase |
| Technical Debt | Clean code | Some debt | Legacy, no tests |
| Factor | Low (1) | Medium (3) | High (5) |
|---|---|---|---|
| Users Affected | Admin only | Department | All users |
| Revenue | None | Indirect | Direct (checkout) |
| Safety | Convenience | Data loss | Physical harm |
| Reputation | Internal | Industry | Public scandal |
Feature | Probability | Impact | Risk | Priority
--------|-------------|--------|------|----------
Checkout | 4 | 5 | 20 | Critical
User Auth | 3 | 5 | 15 | High
Admin Panel | 2 | 2 | 4 | Low
Search | 3 | 3 | 9 | Medium
await Task("Risk-Based Test Generation", {
critical: {
features: ['checkout', 'payment'],
depth: 'comprehensive',
techniques: ['unit', 'integration', 'e2e', 'performance', 'security']
},
high: {
features: ['auth', 'user-profile'],
depth: 'thorough',
techniques: ['unit', 'integration', 'e2e']
},
medium: {
features: ['search', 'notifications'],
depth: 'standard',
techniques: ['unit', 'integration']
},
low: {
features: ['admin-panel', 'settings'],
depth: 'smoke',
techniques: ['smoke-tests']
}
}, "qe-test-generator");
// Production incident increases risk
await Task("Update Risk Score", {
feature: 'search',
event: 'production-incident',
previousRisk: 9,
newProbability: 5, // Increased due to incident
newRisk: 15 // Now HIGH priority
}, "qe-regression-risk-analyzer");
// Agent predicts risk using historical data
const riskAnalysis = await Task("ML Risk Analysis", {
codeChanges: changedFiles,
historicalBugs: bugDatabase,
prediction: {
model: 'gradient-boosting',
factors: ['complexity', 'change-frequency', 'author-experience', 'file-age']
}
}, "qe-regression-risk-analyzer");
// Output: 95% accuracy risk prediction per file
aqe/risk-based/
├── risk-scores/* - Current risk assessments
├── historical-bugs/* - Bug patterns by area
├── production-data/* - Incident data for risk
└── coverage-map/* - Test depth by risk level
const riskFleet = await FleetManager.coordinate({
strategy: 'risk-based-testing',
agents: [
'qe-regression-risk-analyzer', // Risk scoring
'qe-test-generator', // Risk-appropriate tests
'qe-production-intelligence', // Production feedback
'qe-quality-gate' // Risk-based gates
],
topology: 'sequential'
});
# Risk-based test selection in pipeline
- name: Risk Analysis
run: aqe risk-analyze --changes ${{ github.event.pull_request.files }}
- name: Run Critical Tests
if: risk.critical > 0
run: npm run test:critical
- name: Run High Tests
if: risk.high > 0
run: npm run test:high
- name: Skip Low Risk
if: risk.low_only
run: npm run test:smoke
Risk = Probability × Impact. Test where bugs hurt most. Critical gets 60%, low gets 5%. Risk is dynamic - reassess with new info. Production incidents raise risk scores.
With Agents: Agents calculate risk using ML on historical data, select risk-appropriate tests, and adjust scores from production feedback. Use agents to maintain dynamic risk profiles at scale.